Neuromodulators provide flexibility for neural circuit operation and behavior. Yet, at any given time, neural circuits are subject to modulation by multiple neurotransmitters and neurohormones. Each modulator elicits its own specific activity pattern, and presumably, co-modulation by multiple substances increases the degree of circuit flexibility. Despite the multitude of possible combinations and relative concentrations, the output of any neural circuit has low variability across individuals under baseline conditions. Even under identical modulatory conditions this would not be obvious, given that the expression levels of the molecular targets of modulators, for example ion channels, can vary substantially across the population. Numerous studies show that multiple modulators can target the same voltage-gated ion channel type or the same synapse. We propose, somewhat counterintuitively, that the presence of multiple convergent neuromodulators at low concentrations in fact reduces population variability of circuit activity, a hypothesis that is supported by preliminary data. We further propose that consistent circuit activity can occur in the presence of different sets of convergent modulators. We examine these hypotheses in the oscillatory pyloric circuit of the crab stomatogastric ganglion (STG), one of the premier systems for the study of neuromodulation. We propose to combine detailed quantitative measurements of circuit output, as well as underlying synaptic and voltage-gated ionic currents, at different concentrations of 5 neuropeptide modulators and a muscarinic agonist. The modulators of interest are known to target the same fast low-threshold voltage-gated inward current, which increases excitability of STG neurons. A subset of the peptide modulators are known to enhance the same synaptic connections, while others have unknown actions on the synapses, which we plan to explore. Electrical coupling conductances also appear to be modulated by the peptides, potentially with nonlinear interactions. We propose experiments to examine the interactions of modulators at these component levels, with a detailed focus on two well studied neuropeptide modulators, proctolin and the crustacean cardioactive peptide. We will use evolutionary algorithm optimization techniques to produce populations of computational models of the pyloric neurons and synapses, based on these data, where each single model produces the same responses, but different models in the population have different levels of ionic conductances, as observed in the biological system. Component models will be used to build circuit models that produce appropriate activity and correct (co-)modulatory responses. These models would allow us to explore how circuit-level population variability may be changed by co-modulation and by component variability. Additionally, the models will enable us to predict how modulation of components gives rise to circuit patterns of activity specific to that modulator. This work would provide a basic framework for understanding the interactions between different convergent neuromodulators, which can help elucidate drug interaction mechanisms in pharmaceutical therapies.